An artificial immune system model for intelligent agents

King, Roger L.; Russ, Samuel H.; Lambert, Aric B.; Reese, Donna

doi:10.1016/s0167-739x(99)00115-6

Cited by 35 publications

(6 citation statements)

References 11 publications

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“…The following AI paradigms are combined within RT-MOVICAB-IDS to perform these tasks:  Multi-agent system: some of the components are wrapped as deliberative agents, capable of learning and evolving with the environment [77]. As described below, they integrate AI techniques and models, becoming intelligent agents [78].…”

Section: Rt-movicab-idsmentioning

confidence: 99%

RT-MOVICAB-IDS: Addressing real-time intrusion detection

Herrero

Navarro

Corchado

et al. 2013

Future Generation Computer Systems

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This study presents a novel Hybrid Intelligent Intrusion Detection System (IDS) known as RT-MOVICAB-IDS that incorporates temporal control. One of its main goals is to facilitate real-time Intrusion Detection, as accurate and swift responses are crucial in this field, especially if automatic abortion mechanisms are running. The formulation of this hybrid IDS combines Artificial Neural Networks (ANN) and Case-Based Reasoning (CBR) within a Multi-Agent System (MAS) to detect intrusions in dynamic computer networks. Temporal restrictions are imposed on this IDS, in order to perform real/execution time processing and assure system response predictability. Therefore, a dynamic real-time multiagent architecture for IDS is proposed in this study, allowing the addition of predictable agents (both reactive and deliberative). In particular, two of the deliberative agents deployed in this system incorporate temporal-bounded CBR. This upgraded CBR is based on an anytime approximation, which allows the adaptation of this Artificial Intelligence paradigm to real-time requirements. Experimental results using real data sets are presented which validate the performance of this novel hybrid IDS.Research highlights: RT-MOVICAB-IDS, a novel hybrid IDS incorporating temporal control, is presented.> Temporal restrictions allow real time processing and system response predictability.> Experimental results using real data sets are presented which validate the performance.

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Section: Rt-movicab-idsmentioning

confidence: 99%

RT-MOVICAB-IDS: Addressing real-time intrusion detection

Herrero

Navarro

Corchado

et al. 2013

Future Generation Computer Systems

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“…The immune system responds to the pathogens in two ways: (i) through a less specific component called innate immunity (that is nonadaptive), and (ii) a more specific component called adaptive immunity. The body provides an immune response primarily through the leukocytes, the most important ones being phagocytes and lymphocytes [22]. As the first line of defense in the innate immune system, the phagocytes engulf the pathogen, internalize and destroy them.…”

Section: Biological Perspectivementioning

confidence: 99%

Applying the Negative Selection Algorithm for Merger and Acquisition Target Identification Theory and Case Study

Paul

Janecek

Neto³

et al. 2013

2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence

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In this paper, we propose a new methodology based on the Negative Selection Algorithm that belongs to the field of Computational Intelligence (specifically, Artificial Immune Systems -AIS) to identify takeover targets. Although considerable research based on customary statistical techniques and some contemporary Computational Intelligence techniques have been devoted to identify takeover targets, most of the existing studies are based upon multiple previous mergers and acquisitions. Contrary to previous research, the novelty of this proposal lies in the methodology's ability to suggest takeover targets for novice firms that are at the beginning of their merger and acquisition spree. We first discuss the theoretical perspective and then provide a case study with details for practical implementation, both capitalizing from unique generalization capabilities of AIS algorithms.

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“…The immune system integrates a wide set of mechanisms: pattern recognition (affinity), clonal selection (cloning the antibodies that best match the antigen), clonal suppression (killing the worst antibodies), mutation (modifying a set of antibodies), affinity maturation (creating a new set of antibodies), learning and memory (storing the successful antibodies). AIA have been successfully used in network security [11], parallel processing [13], image processing [14], robotic [15] and many challenging optimization problems [16].…”

Section: Aiamentioning

confidence: 99%

A multi-objective adaptive immune algorithm for multi-application NoC mapping

Sepulveda

Chau

Gogniat

et al. 2012

Analog Integr Circ Sig Process

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Current SoC design trends are characterized by the integration of larger amount of IPs targeting a wide range of application fields. Such multi-application systems are constrained by a set of requirements. In such scenario network-on-chips (NoC) are becoming more important as the on-chip communication structure. Designing an optimal NoC for satisfying the requirements of each individual application requires the specification of a large set of configuration parameters leading to a wide solution space. It has been shown that IP mapping is one of the most critical parameters in NoC design, strongly influencing the SoC performance. IP mapping has been solved for single application systems using single and multi-objective optimization algorithms. In this paper we propose the use of a multi-objective adaptive immune algorithm (M 2 AIA), an evolutionary approach to solve the multi-application NoC mapping problem. Latency and power consumption were adopted as the target multi-objective functions. To compare the efficiency of our approach, our results are compared with those of the genetic and branch and bound multi-objective mapping algorithms. We tested 11 wellknown benchmarks, including random and real applications, and combines up to 8 applications at the same SoC.The experimental results showed that the M 2 AIA decreases in average the power consumption and the latency 27.3 and 42.1 % compared to the branch and bound approach and 29.3 and 36.1 % over the genetic approach.

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An artificial immune system model for intelligent agents

Cited by 35 publications

References 11 publications

RT-MOVICAB-IDS: Addressing real-time intrusion detection

RT-MOVICAB-IDS: Addressing real-time intrusion detection

Applying the Negative Selection Algorithm for Merger and Acquisition Target Identification Theory and Case Study

A multi-objective adaptive immune algorithm for multi-application NoC mapping

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